Company Overview
Lifesight is a fast-growing SaaS company focused on helping businesses leverage data & AI to improve customer acquisition and retention. We have a team of 130 serving 300+ customers across 5 offices in the US, Singapore, India, Australia, and the UK.Our mission is to make it easy for non-technical marketers to leverage advanced data activation and marketing measurement tools that are powered by AI, to improve their performance and achieve their KPIs. Our product is being adopted rapidly globally and we need the best people onboard the team to accelerate our growth.
About The Role
We are seeking a Data Science Product Manager with a strong background in statistics, engineering, and applied data science. You'll play a pivotal role in shaping our AI-powered marketing measurement products, working at the intersection of data science, statistical modeling, and product strategy.You will translate sophisticated models and experimental frameworks into intuitive, impactful product features that help marketers make data-driven budget decisions. If you're passionate about statistics, comfortable with advanced modeling libraries, and thrive in bringing cutting-edge data science into customer-facing products, this role is for you.
Key Responsibilities
Own Product Discovery : Identify the most critical measurement challenges through research and data exploration. Evaluate opportunities for applying causal inference, Bayesian methods, and experimentation.Drive the Roadmap : Define and prioritize features for advanced analytics areas such as Marketing Mix Modeling, Incrementality Testing, or Attribution, ensuring alignment between user needs, model feasibility, and business value.Bridge Data Science & Product : Partner closely with data scientists to build models using libraries like Meridian, LightweightMMM, Robyn, PyMC, or Stan. Ensure statistical rigor while packaging outputs into scalable, intuitive product workflows.Experimentation & Validation : Design and analyze A/B/n tests, incrementality studies, and holdout experiments. Apply hypothesis testing, causal inference, and experimental design best practices to validate impact.Define & Specify : Write clear product requirements with both technical depth (model assumptions, KPIs, statistical constraints) and business context.Measure & Iterate : Define KPIs not just for adoption but also model performance metrics (fit, calibration, predictive accuracy). Iterate features based on both product usage and model validation.
Who We're Looking For (Qualifications)
- Bachelor's or Master's degree in Data Science, Statistics, Applied Mathematics, Computer Science, or Engineering.
- 5+ years of professional experience in data science, analytics, or technical product management roles.
- Hands-on familiarity with statistical modeling libraries such as Meridian, Lightweight MMM, Robyn, PyMC, or Stan.
- Strong foundations in probability, regression, hypothesis testing, causal inference, and experimental design.
- Experience designing, analyzing, and interpreting experiments (A/B tests, geo-tests, synthetic control, etc.).
- Ability to work with large datasets and interpret model outcomes into actionable product decisions.
- Excellent communication skills - capable of simplifying complex statistical outputs for non-technical stakeholders.
- Demonstrated ability to take features from concept to launch with clear ownership.
Preferred Qualifications (Bonus Points)
- Experience in AdTech, MarTech, or marketing measurement domains.
- Familiarity with Causal Inference frameworks and advanced time-series and regression models.
- Understanding of data pipelines, APIs, and MLOps practices.
- Prior experience in an Agile/Scrum development environment.
(ref:hirist.tech)
